tion compared with lower scoring peers. Understanding this relationship and using these guidelines can help identify and treat patients whose gait dysfunction may be amplified by psychologic distress.Level of Evidence 3.
  30 have more underlying psychological factors that contribute to significantly worse function compared with lower scoring peers. Understanding this relationship and using these guidelines can help identify and treat patients whose gait dysfunction may be amplified by psychologic distress.Level of Evidence 3.
  Prospective cohort.
 
  The aim of this study was to determine the effect of graft type on residual motion and the relationship among residual motion, smoking, and patient-reported outcome (PRO) scores following anterior cervical discectomy and fusion (ACDF).
 
  Although most patients develop solid fusion based on static imaging following ACDF, dynamic imaging has revealed that many patients continue to have residual motion at the arthrodesis.
 
  Forty-eight participants performed dynamic neck flexion/extension and axial rotation within a biplane radiography system 1 year following ACDF (21 one-level, 27 two-level). PRO scores included the Short Form-36, Neck Disability Index, and Cervical Spine Outcomes Questionnaire. An automated model-based tracking process matched subject-specific bone models to the biplane radiographs with sub-millimeter accuracy. Residual motion was measured across the entire arthrodesis site for both one- and two-level fusions in patients who received either allograft or autograft. PatieAdditionally, autograft appears to result in superior outcomes in patients who smoke.Level of Evidence 2.
 Allograft may result in slightly more residual motion at the arthrodesis site 1 year after ACDF.  https://www.selleckchem.com/products/Glycyrrhizic-Acid.html  However, there is minimal evidence that PROs are adversely affected by slightly increased residual motion, suggesting that the current definition of pseudarthrosis correlates poorly with clinically significant findings. Additionally, autograft appears to result in superior outcomes in patients who smoke.Level of Evidence 2.
  An in vivo model to study the effect of an injectable hyaluronic acid (HA) hydrogel following puncture-induced lumbar disc injury in rabbits.
 
  The aim of this study was to determine the efficacy of an injectable HA hydrogel to maintain disc height and tissue hydration, promote structural repair, and attenuate inflammation and innervation in the lumbar discs.
 
  Previously, we have demonstrated that HA hydrogel alleviated inflammation, innervation, and pain to promote disc repair. Nevertheless, the effect of an injectable HA hydrogel in the lumbar disc in a weight-bearing animal model was not performed.
 
  We have adopted a surgically puncture-induced disc injury at lumbar levels in a rabbit model. The discs were grouped into sham, puncture with water injection, and puncture with HA hydrogel injection. Postoperatively, we measured changes in disc height using x-ray. We used magnetic resonance imaging to assess disc degeneration on tissue hydration after euthanasia. Post-mortem, we determined histological chan.Level of Evidence N/A.
 An injectable HA hydrogel had the protective effects in suppressing the loss of disc height, promoting tissue hydration for structural repair, and attenuating inflammation and innervation to prevent further disc degeneration.Level of Evidence N/A.
  While the COVID-19 pandemic has added stressors to the lives of healthcare workers, it is unclear which factors represent the most useful targets for interventions to mitigate employee distress across the entire healthcare team. A survey was distributed to employees of a large healthcare system in the Southeastern United States, and 1,130 respondents participated. The survey measured overall distress using the 9-item Well-Being Index (WBI), work-related factors, moral distress, resilience, and organizational-level factors. Respondents were also asked to identify major work, clinical, and nonwork stressors. Multivariate regression was used to evaluate associations between employee characteristics and WBI distress score. Overall, 82% of employees reported high distress (WBI ≥ 2), with nurses, clinical support staff, and advanced practice providers reporting the highest average scores. Factors associated with higher distress included increased job demands or responsibilities, heavy workload or long hours, highntly associated with distress-heavy workloads and long hours, increased job demands, and moral distress, in particular-were work-related, indicating that efforts can be made to mitigate them. Resilience explained a small portion of the variance in distress relative to other work-related factors. Ensuring appropriate staffing levels may represent the single largest opportunity to significantly move the needle on distress. However, the financial impact of the COVID-19 pandemic on the healthcare system may represent a barrier to addressing these stressors.
  Since the early 1970s, technology has increasingly become integrated into the healthcare field. Today, artificial intelligence (AI) and machine learning (ML, a set of learning techniques used by AI) have the capacity to revolutionize the delivery of patient care. This essay examines the mechanics and processes of machine learning through discussion of deep learning and natural language processing and then discusses the application of these learning techniques in pattern recognition of malignant tumors in comparison to present methods of diagnostic imaging assessment. The discussion also covers the implications of AI assistive technology more broadly regarding ethical policy making, patient autonomy, and the healthcare Iron Triangle of cost, quality, and access. It concludes with the idea that failure to incorporate AI and ML techniques in healthcare may be malpractice.
 Since the early 1970s, technology has increasingly become integrated into the healthcare field. Today, artificial intelligence (AI) and machine learning (ML, a set of learning techniques used by AI) have the capacity to revolutionize the delivery of patient care. This essay examines the mechanics and processes of machine learning through discussion of deep learning and natural language processing and then discusses the application of these learning techniques in pattern recognition of malignant tumors in comparison to present methods of diagnostic imaging assessment. The discussion also covers the implications of AI assistive technology more broadly regarding ethical policy making, patient autonomy, and the healthcare Iron Triangle of cost, quality, and access. It concludes with the idea that failure to incorporate AI and ML techniques in healthcare may be malpractice.